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Optimal Strategy for Aircraft Pursuit-evasion Games via Self-play Iteration

Machine Intelligence Research 2024年第3期21卷 585-596页

作者： Xin Wang Qing-Lai Wei Tao Li Jie Zhang State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing100049China Institute of Systems Engineering Macao University of Science and TechnologyMacao999078China

In this paper,the pursuit-evasion game with state and control constraints is solved to achieve the Nash equilibrium of both the pursuer and the evader with an iterative self-play *** the condition where the Hamiltonian formed by means of Pontryagin’s maximum principle has the unique solution,it can be proven that the iterative control law converges to the Nash equilibrium ***,the strong nonlinearity of the ordinary differential equations formulated by Pontryagin’s maximum principle makes the control policy difficult to figured *** the system dynamics employed in this manuscript contains a high dimensional state vector with *** practical applications,such as the control of aircraft,the provided overload is ***,in this paper,we consider the optimal strategy of pursuit-evasion games with constant constraint on the control,while some state vectors are restricted by the function of the *** address the challenges,the optimal control problems are transformed into nonlinear programming problems through the direct collocation ***,two numerical cases of the aircraft pursuit-evasion scenario are given to demonstrate the effectiveness of the presented method to obtain the optimal control of both the pursuer and the evader.

关键词： Differential games pursuit-evasion games nonlinear control optimal control Nash equilibrium solution

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Resilient Formation control Based on Watermarks for Networked Quadrotors under Deception Attacks

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IEEE Transactions on Vehicular Technology 2025年第6期74卷 8839-8850页

作者： Zhan, Weiwei Miao, Zhiqiang Zeng, Jianxin Chen, Yanjie Wu, Zheng-Guang He, Wei Wang, Yaonan Hunan University College of Electrical and Information Engineering Changsha410082 China Fuzhou University School of Mechanical Engineering and Automation Fuzhou350108 China National Engineering Research Center of Robot Visual Perception and Control Technology Changsha410082 China Zhejiang University Institute of Cyber-Systems and Control Hangzhou310027 China University of Science and Technology Beijing Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of Education School of Intelligence Science and Technology Institute of Artificial Intelligence Beijing100083 China

This article addresses the problem of formation control of networked UAVs under deception attacks. A lightweight resilient formation control framework based on watermarks is proposed to achieve the desired formation configuration without extra monitoring attack status. Since deception attacks are covert, the shared information is watermarked before transmission to establish the protocol among networked UAVs. To facilitate the resilient formation controller design, a decoder is first developed to decipher the inverse transformation of deception attacks, where the watermark is the criterion for approximating the inverse transformation. The Gauss error function is introduced to eliminate some unrealistic input commands under deception attacks, obtaining the predefined input performance. Then, a resilient formation controller is developed to guarantee the global boundedness of all signals within the inner-loop and outerloop system, while the formation error converges to a small neighborhood of zero by solving the linear matrix inequality. Two challenging deception attack examples in simulations and experiments are conducted to verify the effectiveness and performance of the proposed resilient formation control framework. © 1967-2012 IEEE.

关键词： Inverse transforms

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Comparative study of several PID parameter tuning methods 10

Comparative study of several PID parameter tuning methods

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10th International Conference on Mechanical engineering, Materials, and automation Technology, MMEAT 2024

作者： Zhang, Sai Hu, Shaolin Ke, Ye Chen, Zhihan School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132000 China Automation School Guangdong University of Petrochemical Technology Guangdong Maoming52500 China

ISBN: (纸本)9781510682634

PID (Proportional Integral Derivative) control, as a classical control method, is widely used in petrochemical, metal smelting, food production and other industrial fields due to its superior control performance. With the continuous improvement of industrial production process, the process control environment is becoming more and more complex, and the controlled object often has complex characteristics such as multivariate coupling, large time lag, nonlinearity, multifactor interference, etc. Therefore, the research of PID parameter tuning method has been paid more and more attention, and it has become an important research topic in the field of automatic control. This paper reviews and analyzes Z-N empirical formula method, Critical Ratio method, Cohen-Coon method, ISTE method, fuzzy algorithm and adaptive particle swarm optimization (APSO) algorithm several PID parameter tuning methods, and applies the MATLAB software to analyze the effect of different tuning methods on the performance of the system through the simulation of Simulink comparison experiments. In this paper, the second-order system is used as the control object, and the experimental results show that the APSO PID parameter self-tuning is better than the other methods in the experiments of response performance analysis, tracking performance analysis, and robustness analysis in terms of rise time, overshooting amount, stabilization time and robustness, all of them are better than the other methods. © 2024 SPIE.

关键词： MATLAB

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Detection of Melanoma Based on Improved YOLOv8 13

Detection of Melanoma Based on Improved YOLOv8

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Ji, Honghai Zheng, Xuechen Xiong, Shuangshuang Fan, Lingling Wang, Li School of Electronics & Control Engineering North China University of Technology Beijing100144 China School of Automation Beijing Information Science and Technology University Beijing100096 China

ISBN: (纸本)9798350361674

The incidence of skin cancer is increasing globally, with melanoma being the most formidable form of skin cancer. Melanoma originates from melanocytes, which exhibit a high degree of visual similarity. Moreover, dermoscopy image data often suffer from hair occlusion and the lesion area appears relatively small in the images, making it challenging for traditional methods to achieve accurate recognition and detection results. In this regard, we propose a YOLOv8 framework based on multi-scale sequence fusion(MSSF) for melanoma detection. This approach enhances the Neck structure of YOLOv8 and improves the network's ability to extract multi-scale information by introducing the Multi-scale Sequence Fusion module. In addition, we implemented a morphological black hat based hair processing method to reduce hair occlusion. In the ISIC datasets, compared with the unimproved algorithm, the mean average precision(Map) at 50 IoU is increased by 5.7%, Map between 50 and 95 IoU is increased by 7.5%, and the number of parameters is decreased by 12.5%. © 2024 IEEE.

关键词： Lung cancer

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Estimation of Plant Growth Environment Temperature based on Plant Electrical Signals 7

Estimation of Plant Growth Environment Temperature based on ...

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7th IEEE Information Technology, Networking, Electronic and automation control Conference, ITNEC 2024

作者： Wang, Yifan Tian, Liguo Li, Meng College of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin300222 China Tianjin Key Laboratory of Information Sensing & Intelligent Control Tianjin300222 China

ISBN: (纸本)9798350370782

Electrical signals are an important type of signals in plants, which can not only regulate normal physiological activities, but also reflect the current environmental temperature of plants to a certain extent. The plant electrical signal was collected and the Peak value, Peak to peak and Mean value were extracted as eigenvalues, and the BP neural network was trained to obtain the correspondence model between the eigenvalues of the signal and the ambient temperature. The mean square deviation (MSE) and correlation coefficient (R) of the trained BP neural network model were 0.0058 and 0.9408, respectively. In the re-collected data, 90% of the estimated values fall between 01, and the judgment effect is good, which proves that the model has a high accuracy of judgment. In the future, plant electrical signals can be combined with neural network models to detect temperature, humidity and other parameters in plant growth states, which has high application value in smart agriculture. © 2024 IEEE.

关键词： BP neural network model judgment plant electrical signals relational model smart agriculture Temperature detection

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Master-slave game-based optimal operation of microgrids containing customer-owned photovoltaics 8

Master-slave game-based optimal operation of microgrids cont...

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8th International Conference on Energy System, Electricity, and Power, ESEP 2023

作者： Liu, Xinyue Ji, Yuehui Shi, Shaobo Liu, Junjie Gao, Qiang Xu, Zhao Tianjin Key Laboratory of Complex System Control Theory and Application TJ 300384 China School of Electrical Engineering and Automation Tianjin University of Technology TJ 300384 China

ISBN: (数字)9781510679801

ISBN: (纸本)9781510679795

Due to the dispersed and disorderly feathers of distributed photovoltaic (PV) power generation on the user side, the difficulties of the low-carbon transformation of the power grid and sustainable development of large-scale distributed PV power generation is increased. Based on a master-slave game, this article proposes an optimizing scheme for the operation of microgrids, where the users built PV and shared energy storages. Firstly, this paper introduces the operational framework of the system and the functions of micro-network operator (MNO) and load aggregator (LA). The optimization operation models for MNO and LA are modelled in the framework of Stackelberg master-slave game. The game relationship between MNO and LA is analyzed. Yalmip tool with the CPLEX solver are introduced to solve the differential evolution algorithm. Final, the effectiveness of the proposed method is verified in numerical examples. © 2024 SPIE.

关键词： Energy storage

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Heterogeneous Image Knowledge Driven Visual Perception

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 255-257页

作者： Lan Yan Wenbo Zheng Fei-Yue Wang IEEE the College of Computer Science and Electronic Engineering Hunan UniversityChangsha 410082China the School of Computer Science and Artificial Intelligence Wuhan University of TechnologyWuhan 430070China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter is concerned with visual perception closely related to heterogeneous *** the huge challenge brought by different image modalities,we propose a visual perception framework based on heterogeneous image knowledge,i.e.,the domain knowledge associated with specific vision tasks,to better address the corresponding visual perception problems.

关键词： Visual visual knowledge

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Cooperative Advantage Actor-Critic Reinforcement Learning for Multiagent Pursuit-Evasion Games on Communication Graphs

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6509-6523页

作者： Meng, Yizhen Liu, Chun Wang, Qiang Tan, Longyu Shanghai Aerospace Control Technology Institute Shanghai201109 China Shanghai Key Laboratory of Aerospace Intelligent Control Technology Shanghai201109 China Shanghai University School of Mechatronic Engineering and Automation Shanghai200444 China Shanghai University Institute of Artificial Intelligence Shanghai200444 China Northwestern Polytechnical University College of Astronautics Xi'an710072 China

This article investigates the distributed optimal strategy problem in multiagent pursuit-evasion (MPE) games, striving for Nash equilibrium through the optimization of individual benefit matrices based on observations. To this end, a novel collaborative control scheme for MPE games using communication graphs is proposed. This scheme employs cooperative advantage actor-critic (A2C) reinforcement learning to facilitate collaborative capture by pursuers in a distributed manner while maintaining bounded system signals. The strategy orchestrates the actions of pursuers through adaptive neural network learning, ensuring proximity-based collaboration for effective captures. Meanwhile, evaders aim to evade collectively by converging toward each other. Through extensive simulations involving five pursuers and two evaders, the efficacy of the proposed approach is demonstrated, and pursuers seamlessly organize into pursuit units and capture evaders, validating the collaborative capture objective. This article represents a promising step toward effective and cooperative control strategies in MPE game scenarios. © 2024 IEEE.

关键词： Reinforcement learning

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Multi Classification Online Monitoring of Photovoltaic Array Fault Diagnosis Algorithm

Multi Classification Online Monitoring of Photovoltaic Array...

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2024 China automation Congress, CAC 2024

作者： Liu, Liming Kang, Lingtong Deng, Xiuchang Zheng, Meilin Liu, Jing Shao, Weiming School of Electrical Engineering and Automation Xiamen University of Technology Xiamen China School of Nuclear Science and Technology University of South China Hengyang China School of Electrical Engineering and Automation Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen University of Technology Xiamen China

ISBN: (纸本)9798350368604

With the rapid development of photovoltaic power generation, the fault of photovoltaic array is receiving increasing attention. In response to this issue, proposes an online monitoring photovoltaic array fault diagnosis algorithm based on Support Vector Machines. Firstly, collect the voltage and current of the photovoltaic array for feature extraction. Next, the extracted feature data is normalized and input into a SVM to train the classifier and identify and judge the faults that occur. In the experiment, simulation datasets were used for testing, and online detection and verification were conducted on the real datasets generated by the actual prototype. The results showed that this method can effectively diagnose photovoltaic array faults, with high accuracy and reliability. The online detection photovoltaic array fault diagnosis method based on support vector machine proposed in this paper has high fault detection rate and accuracy, which can provide technical support and guarantee for the maintenance and management of photovoltaic power generation system. © 2024 IEEE.

关键词： Power distribution faults

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Research on operation optimization of rural hybrid renewable energy systems based on Nash bargaining 8

Research on operation optimization of rural hybrid renewable...

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8th International Conference on Energy System, Electricity, and Power, ESEP 2023

作者： Zhuang, Xin Gao, Qiang Xu, Zhao Chen, Jiaqi Zhang, Zhengyang Liu, Junjie College of Electrical Engineering and Automation Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory of Complex System Control Theory and Applications Tianjin300384 China

ISBN: (数字)9781510679801

ISBN: (纸本)9781510679795

The Rural Hybrid Renewable Energy System (RHRES) holds great significance as a prospective energy system development. Ensuring its economic viability and low-carbon operation is crucial in order to fully harness its potential. Consequently, this research paper presents a multi-party cooperation operation model for RHRES, based on the Nash bargaining theory. To effectively differentiate between the various parties involved in carbon trading and guarantee the system's low-carbon operation, a ladder-type multi-party carbon trading model is formulated. The proposed RHRES cooperation operation model, grounded in Nash bargaining, is approached in two steps: determining the transaction volume between parties and resolving the transaction price through the concept of equivalent transformation. To address concerns regarding party privacy, the alternating direction multiplier method is employed for solution. The numerical findings demonstrate that the suggested cooperation operation model substantially reduces RHRES operating costs and carbon emissions, while enhancing the utilization of wind and solar power. Consequently, this model holds significant practical and promotional value. © 2024 SPIE.

关键词： Solar energy

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